Find Jobs
Find Jobs Near You – Available Work in Your Location
Skip to job details
B
BNY
AI Platform Production Engineer
Career Insights for Platform Engineer
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on Florida data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Platform Engineer is responsible for the development of platforms that support the needs and use cases of different engineering teams across the organization. Creates reusable tools and workflows to streamline operational needs and facilitate automation tasks, supporting scalability of DevOps practices.
$129,943 / year median in Florida
Job Description
hackajob is collaborating with BNY to connect them with exceptional professionals for this role. AI Platform Production Engineer At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what is all about. Join us and be part of something extraordinary. We're seeking a future team member for the role of AI Platform Production Engineer to join our Production Services team. This role is in Lake Mary, LM and Pittsburgh, PA In this role, you'll make an impact in the following ways: Provide hands-on engineering capability to automate deployment, orchestration, and management of AI workloads across cloud environments Build robust monitoring, alerting, and observability across infrastructure, data pipelines, and model operations Strengthening reliability and resiliency through direct implementation of automation, self-service tooling, and self-healing controls Reduce manual operational dependency by embedding engineering discipline into the production services model Enable a scalable, high-performance operating environment aligned to the needs of enterprise AI platforms To be successful in this role, we're seeking the following: Deep technical expertise in DevOps and MLOps foundations for large-scale AI platforms Experience with automation, CI/CD pipelines, observability, recovery mechanisms, and operational tooling for cloud-native environments Proven ability to engineer and operate distributed compute, data pipelines, and deployment automation at scale Strong background in building resilient, self-healing production services for complex AI workloads